1. Larry Kagemann

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    1. Mentioned In 50 Articles

    2. Virtual Averaging Making Nonframe-Averaged Optical Coherence Tomography Images Comparable to Frame-Averaged Images

      Virtual Averaging Making Nonframe-Averaged Optical Coherence Tomography Images Comparable to Frame-Averaged Images
      Purpose : Developing a novel image enhancement method so that nonframe-averaged optical coherence tomography (OCT) images become comparable to active eye-tracking frame-averaged OCT images. Methods : Twenty-one eyes of 21 healthy volunteers were scanned with noneye-tracking nonframe-averaged OCT device and active eye-tracking frame-averaged OCT device. Virtual averaging was applied to nonframe-averaged images with voxel resampling and adding amplitude deviation with 15-time repetitions. Signal-to-noise (SNR), contrast-to-noise ratios (CNR), and the distance between the ...
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    3. Predicting Development of Glaucomatous Visual Field Conversion Using Baseline Fourier-Domain Optical Coherence Tomography

      Predicting Development of Glaucomatous Visual Field Conversion Using Baseline Fourier-Domain Optical Coherence Tomography
      Purpose To predict the development of glaucomatous visual field (VF) defects using Fourier-domain optical coherence tomography (FD-OCT) measurements at baseline visit. Design Multi-center longitudinal observational study. Glaucoma suspects and pre-perimetric glaucoma participants in the Advanced Imaging for Glaucoma Study. Methods The optic disc, the peripapillary retinal nerve fiber layer (NFL), and macular ganglion cell complex (GCC) were imaged with FD-OCT VF was assessed every 6 months. Conversion to perimetric glaucoma ...
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    4. Histogram Matching Extends Acceptable Signal Strength Range on Optical Coherence Tomography Images

      Histogram Matching Extends Acceptable Signal Strength Range on Optical Coherence Tomography Images
      Purpose. We minimized the influence of image quality variability, as measured by signal strength (SS), on optical coherence tomography (OCT) thickness measurements using the histogram matching (HM) method. Methods. We scanned 12 eyes from 12 healthy subjects with the Cirrus HD-OCT device to obtain a series of OCT images with a wide range of SS (maximal range, 110) at the same visit. For each eye, the histogram of an image ...
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    5. In Vivo Three-Dimensional Characterization of the Healthy Human Lamina Cribrosa with Adaptive Optics Spectral-Domain Optical Coherence Tomography

      In Vivo Three-Dimensional Characterization of the Healthy Human Lamina Cribrosa with Adaptive Optics Spectral-Domain Optical Coherence Tomography
      Purpose: To characterize the in vivo 3D lamina cribrosa (LC) microarchitecture of healthy eyes using adaptive optics spectral-domain optical coherence tomography (AO-SDOCT). Methods: One randomly selected eye from each of 18 healthy subjects was scanned with Cirrus HD-OCT and AO-SDOCT centered on the optic nerve head. LC microarchitecture, imaged by the later device, was semi-automatically segmented and quantified for connective tissue volume fraction (CTVF), beam thickness, pore diameter, pore area ...
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    6. A Method to Estimate Biomechanics and Mechanical Properties of Optic Nerve Head Tissues From Parameters Measurable Using Optical Coherence Tomography

      A Method to Estimate Biomechanics and Mechanical Properties of Optic Nerve Head Tissues From Parameters Measurable Using Optical Coherence Tomography
      Tissue properties and biomechanics of the optic nerve head (ONH) are important to the development and progression of glaucoma, but remain mostly unmeasurable in the experiment. We hypothesized that these can be estimated numerically from ocular parameters measurable in-vivo with optical coherence tomography (OCT). Using previously reported parametric models representing human ONHs we simulated acute intraocular pressure (IOP) increases (10 mmHg). Statistical models were fit to predict, from OCT-measurable parameters ...
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    7. Repeatability of in vivo 3D lamina cribrosa microarchitecture using adaptive optics spectral domain optical coherence tomography

      Repeatability of in vivo 3D lamina cribrosa microarchitecture using adaptive optics spectral domain optical coherence tomography
      ...dler,^1 Bo Wang,^1,^2 Gadi Wollstein,^1,^* Jessica E. Nevins,^1 Hiroshi Ishikawa,^1,^2 Richard Bilonick,^1,^2 Larry Kagemann,^1,^2 Ian A. Sigal,^1,^2 R. Daniel Ferguson,^3 Ankit Patel,^3 Daniel X. Hammer,^4 and Joel S. S...
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    8. In Vivo Lamina Cribrosa Micro-Architecture in Healthy and Glaucomatous Eyes as Assessed by Optical Coherence Tomography

      In Vivo Lamina Cribrosa Micro-Architecture in Healthy and Glaucomatous Eyes as Assessed by Optical Coherence Tomography
      ...E. Nevins^1, 3. Zach Nadler^1, 4. Gadi Wollstein^1, 5. Hiroshi Ishikawa^1,^2, 6. Richard A. Bilonick^1,^3, 7. Larry Kagemann^1,^2, 8. Ian A. Sigal^1,^2, 9. Ireneusz Grulkowski^4, 10. Jonathan J. Liu^4, 11. Martin Kraus^4...
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    9. In-Vivo Lamina Cribrosa Microarchitecture in Healthy and Glaucomatous Eyes as Assessed by Optical Coherence Tomography

      In-Vivo Lamina Cribrosa Microarchitecture in Healthy and Glaucomatous Eyes as Assessed by Optical Coherence Tomography
      Purpose: Lamina cribrosa (LC) is a leading location of glaucomatous damage. The purpose of this study is to compare LC 3-dimensional microarchitecture between healthy and glaucomatous eyes in-vivo using optical coherence tomography (OCT). Methods: Sixty-eight eyes (19 healthy and 49 glaucomatous) from 47 subjects were scanned in a 3.5x3.5x3.64mm volume (400x400x896 pixels) at the optic nerve head using swept-source OCT. The LC microarchitecture parameters were measured on ...
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    10. Automated lamina cribrosa microstructural segmentation in optical coherence tomography scans of healthy and glaucomatous eyes

      Automated lamina cribrosa microstructural segmentation in optical coherence tomography scans of healthy and glaucomatous eyes
      ...or Affiliations Zach Nadler,^1 Bo Wang,^1,^2 Gadi Wollstein,^1,^* Jessica E. Nevins,^1 Hiroshi Ishikawa,^1,^2 Larry Kagemann,^1,^2 Ian A. Sigal,^1,^2 R. Daniel Ferguson,^3 Daniel X. Hammer,^4 Ireneusz Grulkowski,^5 Jonat...
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    11. Signal Normalization Reduces Systematic Measurement Differences Between Spectral Domain Optical Coherence Tomography Devices

      Signal Normalization Reduces Systematic Measurement Differences Between Spectral Domain Optical Coherence Tomography Devices
      Purpose: To test the effect of a novel signal normalization method for reducing systematic optical coherence tomography (OCT) measurement differences among multiple spectral-domain (SD-) OCT devices. Methods: One hundred and nine eyes from 59 subjects were scanned with two SD-OCT devices (Cirrus and RTVue) at the same visit. OCT image data were normalized to match their signal characteristics between the devices. To compensate signal strength differences, a custom high dynamic ...
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    12. Individual A-scan Signal Normalization Between Two Spectral Domain Optical Coherence Tomography Devices

      Individual A-scan Signal Normalization Between Two Spectral Domain Optical Coherence Tomography Devices
      Purpose: To develop a method to normalize optical coherence tomography (OCT) signal profiles from two spectral-domain (SD-) OCT devices so that the comparability between devices increases. Methods: Twenty-one eyes from 14 healthy and 7 glaucoma subjects were scanned with two SD-OCT devices on the same day with equivalent cube scan patterns centered on the fovea (Cirrus HD-OCT, Carl Zeiss Meditec, Dublin, CA; and RTVue, Optovue, Fremont, CA). Foveola positions were ...
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  2. About Larry Kagemann

    Larry Kagemann

    Lawrence Kagemann is a Research Assistant Professor in the School of Medicine Eye and Ear Institute and the School of Engineering Department of Bioengineering at the University of Pittsburgh.